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computer codes to solve some of the daily research problems and have experience with high performance computing. You should have a PhD in Chemistry, Physics or Materials Science with a proven research track
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no.: 4331 Among the many reasons to research and teach at the University of Vienna there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as
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completion) in AI, Machine Learning, Data Science, Control or Energy Systems Engineering, or a related field. Strong expertise in AI for real-time systems, predictive analytics, or Digital Twins. Experience
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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design, delivery, and evaluation of a multi-school research study investigating the impact of mathematical storytelling on secondary students’ mathematics learning and related outcomes. Working closely
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sustainability, performance, and reliability. Our research leverages optimization techniques, applied machine learning, and statistical analysis to achieve these objectives. Through the DecAI project we will work
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. Responsibilities include working with digital signal processing, advanced filtering techniques, dynamic feature extraction, time-domain and frequency-domain analysis, signal fusion and machine learning to enhance
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strategic dissemination, ultimately aiming for widespread adoption and commercial success. If you are still awaiting your PhD to be awarded you will be appointed at Grade 6, spine point 30. Upon written
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47 Faculty of Psychology Startdate: 05.10.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 04.04.2026 Reference no.: 4360 Explore and teach
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and its end-users. You will remain abreast of new developments in data science and data visualisation, in particular the use of machine learning and AI tools, and their application to IDDO’s model. You